A computer-implemented image manipulation apparatus and method (200) configured to receiving an input image (202) and a desired style. The method can obtain a representation (204) of the input image selected from a plurality of stored representations of a plurality of images, wherein each said representation comprises data describing a set of image features. The method can modify image features in the obtained representation to correspond to the input image and/or the desired style to produce a modified representation (207), and render a reference image (209) based on the modified representation. A manipulated image is generated by performing a style transfer operation (210) on the input image using the rendered reference image. Embodiments may access a data store to find a group of stored images based on similarity between image content descriptors of groups of stored images and those of an input image to retrieve a stored reference image.
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2. The method of claim 1, wherein the plurality of representations comprise a respective plurality of statistical representations, and wherein the image features of the statistical representations comprise common features of the plurality of images identified by a content analysis method performed on the plurality of images.
3. The method of claim 2, wherein the content analysis method is performed by a statistical system to generate the statistical representations of the plurality of images.
4. The method of claim 3, wherein the statistical system comprises a machine learning technique that learns a distribution of the identified common features across the plurality of images.
5. The method of claim 4, wherein the machine learning technique comprises a dimensionality reduction process.
6. The method of claim 3, wherein the of rendering the reference image comprises a reverse of a process used to generate the statistical representations of the plurality of images.
7. The method of claim 6, wherein the reference image comprises a synthetic rendering of the input image.
8. The method of claim 7, wherein the input image comprises a face and the synthetic rendering comprises a 3D rendering of the face.
9. The method of claim 2, wherein the plurality of images comprise a dataset of example images of a particular type, and the set of image features comprise principal features that change across the plurality of images in the dataset.
10. The method of claim 1, wherein the of obtaining the representation of the input image comprises finding a said representation amongst the plurality of stored representations that has a greatest visual similarity to the input image.
12. The method of claim 11, wherein the desired style is based on a style image that provides the value for each of the image features of the desired style.
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May 14, 2020
January 9, 2024
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